Interesting take away by @yoavgo about #dlearn models for QA.pic.twitter.com/lYL4WDwNvN
আপনি আপনার টুইটগুলিতে ওয়েব থেকে এবং তৃতীয়-পক্ষ অ্যাপ্লিকেশনগুলির মাধ্যমে অবস্থান তথ্য যেমন শহর বা সুনির্দিষ্ট অবস্থান যোগ করতে পারবেন। আপনার কাছে আপনার টুইটের অবস্থান ইতিহাস মোছার বিকল্প থাকবে। আরও জানুন
I studied them in depth so I could implement them from scratch and therefore teach them. Was shocked at what I found
What did you find?
1. The problem it was used on (babi) has a couple of dozen unique words (ish), and the 'sentences' have a simple fixed structure
2. The solution embedded lots of problem-specific hacks, such as the ordering of sentences being encoded as a special token
3. The "algorithm" (if it can even be called that) is just a dot product of embeddings
4. The actual tricky bits, like how to create a good sentence or query embedding, are ignored (they just average the word embeddings)
5. The research group literally created an animated gif for the media that implied they could use this to understand Lord Of The Rings
(The main article was by @davegershgorn and is http://www.popsci.com/facebook-ai , but many others too like http://www.slate.com/blogs/business_insider/2015/11/24/facebook_is_teaching_it_s_artificial_intelligence_to_remember_lord_of_the.html … )
Then they took babi and replaced the names with LOTR characters and told the media the algorithm could answer questions about the book :(
I would say GANs are overrated and overhyped not memNets
They may be able to help semi-supervised learning, and they may also be a useful post-processing step for "creative AI". Some potential...
I see it as a glorified attention mechanism. Novel for sure but not sure it's ground breaking
Actual attention mechanisms are much more interesting IMO. @kchonyc's paper pre-dated memory networks, but is far (far far) more impactful
Completely agree. Haven't come across as impactful appl. of MemNets as Seq-Seq+Attn. best I've seen is @DhruvBatraDB labs work on visdial
টুইটার তার ক্ষমতার বাইরে চলে গেছে বা কোনো সাময়িক সমস্যার সম্মুখীন হয়েছে আবার চেষ্টা করুন বা আরও তথ্যের জন্য টুইটারের স্থিতি দেখুন।